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<h2 class="title">
<a id="docvalues"></a>Doc Values<a class="edit_me edit_me_private" rel="nofollow" title="Editing on GitHub is available to Elastic" href="https://github.com/elastic/elasticsearch-definitive-guide/edit/2.x/300_Aggregations/90_docvalues.asciidoc">edit</a>
</h2>
</div></div></div>
<p>Aggregations work via a data structure known as <em>doc values</em> (briefly introduced
in <a class="xref" href="docvalues-intro.html" title="Doc Values Intro">Doc Values Intro</a>).  Doc values
are what make aggregations fast, efficient and memory-friendly, so it is useful
to understand how they work.</p>
<p>Doc values exists because inverted indices are efficient for only certain operations.
The inverted index excels at finding documents that contain a term.  It does not
perform well in the opposite direction: determining which terms exist in a single
document. Aggregations need this secondary access pattern.</p>
<p>Consider the following inverted index:</p>
<pre class="literallayout">Term      Doc_1   Doc_2   Doc_3
------------------------------------
brown   |   X   |   X   |
dog     |   X   |       |   X
dogs    |       |   X   |   X
fox     |   X   |       |   X
foxes   |       |   X   |
in      |       |   X   |
jumped  |   X   |       |   X
lazy    |   X   |   X   |
leap    |       |   X   |
over    |   X   |   X   |   X
quick   |   X   |   X   |   X
summer  |       |   X   |
the     |   X   |       |   X
------------------------------------</pre>

<p>If we want to compile a complete list of terms in any document that mentions
<code class="literal">brown</code>, we might build a query like so:</p>
<div class="pre_wrapper lang-js">
<pre class="programlisting prettyprint lang-js">GET /my_index/_search
{
  "query" : {
    "match" : {
      "body" : "brown"
    }
  },
  "aggs" : {
    "popular_terms": {
      "terms" : {
        "field" : "body"
      }
    }
  }
}</pre>
</div>
<p>The query portion is easy and efficient.  The inverted index is sorted by
terms, so first we find <code class="literal">brown</code> in the terms list, and then scan across all the
columns to see which documents contain <code class="literal">brown</code>.  We can very quickly see that
<code class="literal">Doc_1</code> and <code class="literal">Doc_2</code> contain the token <code class="literal">brown</code>.</p>
<p>Then, for the aggregation portion, we need to find all the unique terms in
<code class="literal">Doc_1</code>  and <code class="literal">Doc_2</code>.  Trying to do this with the inverted index would be a
very expensive process: we would have to iterate over every term in the index
and collect tokens from <code class="literal">Doc_1</code>  and <code class="literal">Doc_2</code> columns.  This would be slow
and scale poorly: as the number of terms and  documents grows, so would the
execution time.</p>
<p>Doc values addresses this problem by inverting the relationship. While the
inverted index maps terms to the documents containing the term, doc values
maps documents to the terms contained by the document:</p>
<pre class="literallayout">Doc      Terms
-----------------------------------------------------------------
Doc_1 | brown, dog, fox, jumped, lazy, over, quick, the
Doc_2 | brown, dogs, foxes, in, lazy, leap, over, quick, summer
Doc_3 | dog, dogs, fox, jumped, over, quick, the
-----------------------------------------------------------------</pre>

<p>Once the data has been uninverted, it is trivial to collect the unique tokens from
<code class="literal">Doc_1</code> and <code class="literal">Doc_2</code>.  Go to the rows for each document, collect all the terms, and
take the union of the two sets.</p>
<p>Thus, search and aggregations are closely intertwined.  Search finds documents
by using the inverted index.  Aggregations collect and aggregate values from
doc values.</p>
<div class="note admon">
<div class="icon"></div>
<div class="admon_content">
<p>Doc values are not just used for aggregations.  They are required for any
operation that must look up the value contained in a specific document.
Besides aggregations, this includes sorting, scripts that access field
values and parent-child relationships (see <a class="xref" href="parent-child.html" title="Parent-Child Relationship"><em>Parent-Child Relationship</em></a>).</p>
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